In supervised learning, the algorithm is given labeled examples in order to come up with an appropriate model that defines the data and can also correctly label future examples correctly (or adequately). Supervised learning can be grouped into the following depending on the actual label type:
- Binary Classification (think yes/no)
- Multi-class classification (any answer from a finite set)
- Rgression (any answer from an infinite set)
In the machine library I am trying to put together, each of the three groups mentioned above can be separated into distinct .NET data types as follows:
I had the priviledge of presenting at CodeStock. It was absolutely great. I was surprised and humbled at the reception of my session regarding Machine Learning. As such, I wanted to do a series of posts regarding what it is I wish to accomplish.
Machine Learning is Hard
Because the stuff is so intriguing, I have spent the last number of years trying to figure the stuff out! I would certainly not classify myself as an expert (by any means), but I think I have a general idea of the field.
Machine learning can be seperated into roughly 3 classifications:
This is part 3 of a series going through the process of creating an advanced control for the ASP.NET MVC system. I’ve decided to create a schedule control that allows a user to schedule and item on a calendar control as well as add some meta-data information to the scheduled date. Together with the debugger we have built, this should not be too difficult